Retraining Classifier Results

This week I worked on retraining the haar cascade. After being able to create 1000 positive samples I used 500 negative samples as input for our narrow helix classifier. The first attempt of training only passed through 1 stage then terminated with the following error "Train dataset for temp stage can not be filled. Branch training terminated."

I learned that this occurred because the paths within my negative descriptor were incorrect,  I quickly fixed this and retrained. On the second attempt stages 0 and 1 were loaded and I was able to enter into stage 2, but once again I encountered another issue "Required leaf false alarm rate achieved. Branch training terminated."

The third attempt I made to train the classifier was much more successful than the previous. I ended up starting from scratch without loading the last xml containing the results of prior stages and reached the third stage. I then tried testing the classifier with my detect script, but I was unable to detect any narrow helixes in my sample image.

Even though I wasn't able to detect helixes within my test images, we've made meaningful progress in training the classifier. Prior to now training didn't proceed past the 1st stage. With some minor adjustments we should be able to accurately detect segments of the ear.

Project Update February 22nd

I did not blog about the project last week.

This week we met with a grad research student, Ayotunde. He provided some great insights and assisted us in moving further with the project. I was able to generate over 1000 images from one positive sample image.

This breakthrough will allow us to provide more sample images when training our classifier. The issue that prevented us from properly detecting parts of the ear was the poor accuracy of our cascade. During training our sample size was too small to go through many stages. Once I can create a larger amount of negative samples I will be able to build a more accurate cascade.

Cascade Training in Windows Environment

Last week we discussed the possibility of switching our tools used for training our haar cascade classifier. Over the course of the week we set up two computers with the required software for building a classifier. The resources we used to assist us with the setup included two computer vision blogs. Links: [1] [2]

I was successful in gathering a small sample of images and recreating most of the progress we previously experienced, but the haartraining consistently failed. Currently I'm experiencing a parse error with generating the .vec file. (Figure Below)

Setting up the windows environment wasn't as easy as I anticipated and the results didn't exceed the progress we made before. By next week I plan on resolving the create samples issue I experienced on the Mac environment. I will reach out to the openCV community through forums and emails for additional advice. After fixing this issue I plan on generating a large sample of images ~500 and follow the advised testing ratios and criteria mentioned in my previous post.

Weekly Recap Meeting

Today Morgan and I met with Dr. Washington. We discussed our current problems with the project and next steps to take. I'm currently trying to convert all my positive samples to 8-bit images, this may improve our cascade. We reached out to another research group who had experienced building classifiers for advice. Also we contemplated on using different tools to help with our project as well, in the next few days we will trying using a windows environment to train our cascade to see if we obtain better results.